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Welcome to LineageTree Documentation

LineageTree is a Python framework designed for the analysis of cell-tracking data. It supports both standard and custom tracking formats and enables comprehensive temporal and spatial analysis.

Why should I use LineageTree?

Understanding how a cluster of cells becomes a structured organism is a foundational question in developmental biology. Modern microscopy now allows researchers to image embryos in real time, and many tools exist for tracking nuclei or particles over time. However, most available software focuses primarily on spatial positions and lacks robust support for analyzing temporal structure and division patterns within lineages. LineageTree aims to fill this gap by providing built-in algorithms that compare lineage data using both temporal and spatial information. At the same time, it offers a robust and extensible foundation that allows users to implement their own analysis methods, while supporting most popular tracking formats.

Using LineageTree the user can:

Unordered Tree Edit Distance (UTED)

One of the core analysis algorithms provided by this module is UTED, which quantifies how similar or dissimilar two lineages are. Calculating lineage distances is a powerful way to analyze developmental variability, identify fate gain or loss, and detect lineage symmetry within a single organism.

This framework is complemented by the napari plugin ReLAX. ReLAX allows users to explore a digital representation of the embryo across both space and time, annotate its lineages, and perform systematic comparisons on imported lineage data. Together, these tools offer an integrated environment for visualizing, labeling, and analyzing lineage structures with temporal and spatial context.

Quick Installation

pip install LineageTree

Content

Getting started: Installation guide

Glossary: Contains all the different nomenclature the project is using and shows the connection with biological lineages.